Actual source code: ex3.c


  2: static char help[] = "Solves a simple time-dependent linear PDE (the heat equation).\n\
  3: Input parameters include:\n\
  4:   -m <points>, where <points> = number of grid points\n\
  5:   -time_dependent_rhs : Treat the problem as having a time-dependent right-hand side\n\
  6:   -use_ifunc          : Use IFunction/IJacobian interface\n\
  7:   -debug              : Activate debugging printouts\n\
  8:   -nox                : Deactivate x-window graphics\n\n";

 10: /* ------------------------------------------------------------------------

 12:    This program solves the one-dimensional heat equation (also called the
 13:    diffusion equation),
 14:        u_t = u_xx,
 15:    on the domain 0 <= x <= 1, with the boundary conditions
 16:        u(t,0) = 0, u(t,1) = 0,
 17:    and the initial condition
 18:        u(0,x) = sin(6*pi*x) + 3*sin(2*pi*x).
 19:    This is a linear, second-order, parabolic equation.

 21:    We discretize the right-hand side using finite differences with
 22:    uniform grid spacing h:
 23:        u_xx = (u_{i+1} - 2u_{i} + u_{i-1})/(h^2)
 24:    We then demonstrate time evolution using the various TS methods by
 25:    running the program via
 26:        ex3 -ts_type <timestepping solver>

 28:    We compare the approximate solution with the exact solution, given by
 29:        u_exact(x,t) = exp(-36*pi*pi*t) * sin(6*pi*x) +
 30:                       3*exp(-4*pi*pi*t) * sin(2*pi*x)

 32:    Notes:
 33:    This code demonstrates the TS solver interface to two variants of
 34:    linear problems, u_t = f(u,t), namely
 35:      - time-dependent f:   f(u,t) is a function of t
 36:      - time-independent f: f(u,t) is simply f(u)

 38:     The parallel version of this code is ts/tutorials/ex4.c

 40:   ------------------------------------------------------------------------- */

 42: /*
 43:    Include "petscts.h" so that we can use TS solvers.  Note that this file
 44:    automatically includes:
 45:      petscsys.h       - base PETSc routines   petscvec.h  - vectors
 46:      petscmat.h  - matrices
 47:      petscis.h     - index sets            petscksp.h  - Krylov subspace methods
 48:      petscviewer.h - viewers               petscpc.h   - preconditioners
 49:      petscksp.h   - linear solvers        petscsnes.h - nonlinear solvers
 50: */

 52: #include <petscts.h>
 53: #include <petscdraw.h>

 55: /*
 56:    User-defined application context - contains data needed by the
 57:    application-provided call-back routines.
 58: */
 59: typedef struct {
 60:   Vec         solution;         /* global exact solution vector */
 61:   PetscInt    m;                /* total number of grid points */
 62:   PetscReal   h;                /* mesh width h = 1/(m-1) */
 63:   PetscBool   debug;            /* flag (1 indicates activation of debugging printouts) */
 64:   PetscViewer viewer1, viewer2; /* viewers for the solution and error */
 65:   PetscReal   norm_2, norm_max; /* error norms */
 66:   Mat         A;                /* RHS mat, used with IFunction interface */
 67:   PetscReal   oshift;           /* old shift applied, prevent to recompute the IJacobian */
 68: } AppCtx;

 70: /*
 71:    User-defined routines
 72: */
 73: extern PetscErrorCode InitialConditions(Vec, AppCtx *);
 74: extern PetscErrorCode RHSMatrixHeat(TS, PetscReal, Vec, Mat, Mat, void *);
 75: extern PetscErrorCode IFunctionHeat(TS, PetscReal, Vec, Vec, Vec, void *);
 76: extern PetscErrorCode IJacobianHeat(TS, PetscReal, Vec, Vec, PetscReal, Mat, Mat, void *);
 77: extern PetscErrorCode Monitor(TS, PetscInt, PetscReal, Vec, void *);
 78: extern PetscErrorCode ExactSolution(PetscReal, Vec, AppCtx *);

 80: int main(int argc, char **argv)
 81: {
 82:   AppCtx      appctx;                 /* user-defined application context */
 83:   TS          ts;                     /* timestepping context */
 84:   Mat         A;                      /* matrix data structure */
 85:   Vec         u;                      /* approximate solution vector */
 86:   PetscReal   time_total_max = 100.0; /* default max total time */
 87:   PetscInt    time_steps_max = 100;   /* default max timesteps */
 88:   PetscDraw   draw;                   /* drawing context */
 89:   PetscInt    steps, m;
 90:   PetscMPIInt size;
 91:   PetscReal   dt;
 92:   PetscBool   flg, flg_string;

 94:   /* - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
 95:      Initialize program and set problem parameters
 96:      - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - */

 99:   PetscInitialize(&argc, &argv, (char *)0, help);
100:   MPI_Comm_size(PETSC_COMM_WORLD, &size);

103:   m = 60;
104:   PetscOptionsGetInt(NULL, NULL, "-m", &m, NULL);
105:   PetscOptionsHasName(NULL, NULL, "-debug", &appctx.debug);
106:   flg_string = PETSC_FALSE;
107:   PetscOptionsGetBool(NULL, NULL, "-test_string_viewer", &flg_string, NULL);

109:   appctx.m        = m;
110:   appctx.h        = 1.0 / (m - 1.0);
111:   appctx.norm_2   = 0.0;
112:   appctx.norm_max = 0.0;

114:   PetscPrintf(PETSC_COMM_SELF, "Solving a linear TS problem on 1 processor\n");

116:   /* - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
117:      Create vector data structures
118:      - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - */

120:   /*
121:      Create vector data structures for approximate and exact solutions
122:   */
123:   VecCreateSeq(PETSC_COMM_SELF, m, &u);
124:   VecDuplicate(u, &appctx.solution);

126:   /* - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
127:      Set up displays to show graphs of the solution and error
128:      - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - */

130:   PetscViewerDrawOpen(PETSC_COMM_SELF, 0, "", 80, 380, 400, 160, &appctx.viewer1);
131:   PetscViewerDrawGetDraw(appctx.viewer1, 0, &draw);
132:   PetscDrawSetDoubleBuffer(draw);
133:   PetscViewerDrawOpen(PETSC_COMM_SELF, 0, "", 80, 0, 400, 160, &appctx.viewer2);
134:   PetscViewerDrawGetDraw(appctx.viewer2, 0, &draw);
135:   PetscDrawSetDoubleBuffer(draw);

137:   /* - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
138:      Create timestepping solver context
139:      - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - */

141:   TSCreate(PETSC_COMM_SELF, &ts);
142:   TSSetProblemType(ts, TS_LINEAR);

144:   /* - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
145:      Set optional user-defined monitoring routine
146:      - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - */

148:   if (!flg_string) TSMonitorSet(ts, Monitor, &appctx, NULL);

150:   /* - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -

152:      Create matrix data structure; set matrix evaluation routine.
153:      - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - */

155:   MatCreate(PETSC_COMM_SELF, &A);
156:   MatSetSizes(A, PETSC_DECIDE, PETSC_DECIDE, m, m);
157:   MatSetFromOptions(A);
158:   MatSetUp(A);

160:   flg = PETSC_FALSE;
161:   PetscOptionsGetBool(NULL, NULL, "-use_ifunc", &flg, NULL);
162:   if (!flg) {
163:     appctx.A = NULL;
164:     PetscOptionsGetBool(NULL, NULL, "-time_dependent_rhs", &flg, NULL);
165:     if (flg) {
166:       /*
167:          For linear problems with a time-dependent f(u,t) in the equation
168:          u_t = f(u,t), the user provides the discretized right-hand-side
169:          as a time-dependent matrix.
170:       */
171:       TSSetRHSFunction(ts, NULL, TSComputeRHSFunctionLinear, &appctx);
172:       TSSetRHSJacobian(ts, A, A, RHSMatrixHeat, &appctx);
173:     } else {
174:       /*
175:          For linear problems with a time-independent f(u) in the equation
176:          u_t = f(u), the user provides the discretized right-hand-side
177:          as a matrix only once, and then sets the special Jacobian evaluation
178:          routine TSComputeRHSJacobianConstant() which will NOT recompute the Jacobian.
179:       */
180:       RHSMatrixHeat(ts, 0.0, u, A, A, &appctx);
181:       TSSetRHSFunction(ts, NULL, TSComputeRHSFunctionLinear, &appctx);
182:       TSSetRHSJacobian(ts, A, A, TSComputeRHSJacobianConstant, &appctx);
183:     }
184:   } else {
185:     Mat J;

187:     RHSMatrixHeat(ts, 0.0, u, A, A, &appctx);
188:     MatDuplicate(A, MAT_DO_NOT_COPY_VALUES, &J);
189:     TSSetIFunction(ts, NULL, IFunctionHeat, &appctx);
190:     TSSetIJacobian(ts, J, J, IJacobianHeat, &appctx);
191:     MatDestroy(&J);

193:     PetscObjectReference((PetscObject)A);
194:     appctx.A      = A;
195:     appctx.oshift = PETSC_MIN_REAL;
196:   }
197:   /* - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
198:      Set solution vector and initial timestep
199:      - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - */

201:   dt = appctx.h * appctx.h / 2.0;
202:   TSSetTimeStep(ts, dt);

204:   /* - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
205:      Customize timestepping solver:
206:        - Set the solution method to be the Backward Euler method.
207:        - Set timestepping duration info
208:      Then set runtime options, which can override these defaults.
209:      For example,
210:           -ts_max_steps <maxsteps> -ts_max_time <maxtime>
211:      to override the defaults set by TSSetMaxSteps()/TSSetMaxTime().
212:      - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - */

214:   TSSetMaxSteps(ts, time_steps_max);
215:   TSSetMaxTime(ts, time_total_max);
216:   TSSetExactFinalTime(ts, TS_EXACTFINALTIME_STEPOVER);
217:   TSSetFromOptions(ts);

219:   /* - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
220:      Solve the problem
221:      - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - */

223:   /*
224:      Evaluate initial conditions
225:   */
226:   InitialConditions(u, &appctx);

228:   /*
229:      Run the timestepping solver
230:   */
231:   TSSolve(ts, u);
232:   TSGetStepNumber(ts, &steps);

234:   /* - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
235:      View timestepping solver info
236:      - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - */

238:   PetscPrintf(PETSC_COMM_SELF, "avg. error (2 norm) = %g, avg. error (max norm) = %g\n", (double)(appctx.norm_2 / steps), (double)(appctx.norm_max / steps));
239:   if (!flg_string) {
240:     TSView(ts, PETSC_VIEWER_STDOUT_SELF);
241:   } else {
242:     PetscViewer stringviewer;
243:     char        string[512];
244:     const char *outstring;

246:     PetscViewerStringOpen(PETSC_COMM_WORLD, string, sizeof(string), &stringviewer);
247:     TSView(ts, stringviewer);
248:     PetscViewerStringGetStringRead(stringviewer, &outstring, NULL);
250:     PetscPrintf(PETSC_COMM_WORLD, "Output from string viewer:%s\n", outstring);
251:     PetscViewerDestroy(&stringviewer);
252:   }

254:   /* - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
255:      Free work space.  All PETSc objects should be destroyed when they
256:      are no longer needed.
257:      - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - */

259:   TSDestroy(&ts);
260:   MatDestroy(&A);
261:   VecDestroy(&u);
262:   PetscViewerDestroy(&appctx.viewer1);
263:   PetscViewerDestroy(&appctx.viewer2);
264:   VecDestroy(&appctx.solution);
265:   MatDestroy(&appctx.A);

267:   /*
268:      Always call PetscFinalize() before exiting a program.  This routine
269:        - finalizes the PETSc libraries as well as MPI
270:        - provides summary and diagnostic information if certain runtime
271:          options are chosen (e.g., -log_view).
272:   */
273:   PetscFinalize();
274:   return 0;
275: }
276: /* --------------------------------------------------------------------- */
277: /*
278:    InitialConditions - Computes the solution at the initial time.

280:    Input Parameter:
281:    u - uninitialized solution vector (global)
282:    appctx - user-defined application context

284:    Output Parameter:
285:    u - vector with solution at initial time (global)
286: */
287: PetscErrorCode InitialConditions(Vec u, AppCtx *appctx)
288: {
289:   PetscScalar *u_localptr, h = appctx->h;
290:   PetscInt     i;

292:   /*
293:     Get a pointer to vector data.
294:     - For default PETSc vectors, VecGetArray() returns a pointer to
295:       the data array.  Otherwise, the routine is implementation dependent.
296:     - You MUST call VecRestoreArray() when you no longer need access to
297:       the array.
298:     - Note that the Fortran interface to VecGetArray() differs from the
299:       C version.  See the users manual for details.
300:   */
301:   VecGetArrayWrite(u, &u_localptr);

303:   /*
304:      We initialize the solution array by simply writing the solution
305:      directly into the array locations.  Alternatively, we could use
306:      VecSetValues() or VecSetValuesLocal().
307:   */
308:   for (i = 0; i < appctx->m; i++) u_localptr[i] = PetscSinScalar(PETSC_PI * i * 6. * h) + 3. * PetscSinScalar(PETSC_PI * i * 2. * h);

310:   /*
311:      Restore vector
312:   */
313:   VecRestoreArrayWrite(u, &u_localptr);

315:   /*
316:      Print debugging information if desired
317:   */
318:   if (appctx->debug) {
319:     PetscPrintf(PETSC_COMM_WORLD, "Initial guess vector\n");
320:     VecView(u, PETSC_VIEWER_STDOUT_SELF);
321:   }

323:   return 0;
324: }
325: /* --------------------------------------------------------------------- */
326: /*
327:    ExactSolution - Computes the exact solution at a given time.

329:    Input Parameters:
330:    t - current time
331:    solution - vector in which exact solution will be computed
332:    appctx - user-defined application context

334:    Output Parameter:
335:    solution - vector with the newly computed exact solution
336: */
337: PetscErrorCode ExactSolution(PetscReal t, Vec solution, AppCtx *appctx)
338: {
339:   PetscScalar *s_localptr, h = appctx->h, ex1, ex2, sc1, sc2, tc = t;
340:   PetscInt     i;

342:   /*
343:      Get a pointer to vector data.
344:   */
345:   VecGetArrayWrite(solution, &s_localptr);

347:   /*
348:      Simply write the solution directly into the array locations.
349:      Alternatively, we culd use VecSetValues() or VecSetValuesLocal().
350:   */
351:   ex1 = PetscExpScalar(-36. * PETSC_PI * PETSC_PI * tc);
352:   ex2 = PetscExpScalar(-4. * PETSC_PI * PETSC_PI * tc);
353:   sc1 = PETSC_PI * 6. * h;
354:   sc2 = PETSC_PI * 2. * h;
355:   for (i = 0; i < appctx->m; i++) s_localptr[i] = PetscSinScalar(sc1 * (PetscReal)i) * ex1 + 3. * PetscSinScalar(sc2 * (PetscReal)i) * ex2;

357:   /*
358:      Restore vector
359:   */
360:   VecRestoreArrayWrite(solution, &s_localptr);
361:   return 0;
362: }
363: /* --------------------------------------------------------------------- */
364: /*
365:    Monitor - User-provided routine to monitor the solution computed at
366:    each timestep.  This example plots the solution and computes the
367:    error in two different norms.

369:    This example also demonstrates changing the timestep via TSSetTimeStep().

371:    Input Parameters:
372:    ts     - the timestep context
373:    step   - the count of the current step (with 0 meaning the
374:              initial condition)
375:    time   - the current time
376:    u      - the solution at this timestep
377:    ctx    - the user-provided context for this monitoring routine.
378:             In this case we use the application context which contains
379:             information about the problem size, workspace and the exact
380:             solution.
381: */
382: PetscErrorCode Monitor(TS ts, PetscInt step, PetscReal time, Vec u, void *ctx)
383: {
384:   AppCtx   *appctx = (AppCtx *)ctx; /* user-defined application context */
385:   PetscReal norm_2, norm_max, dt, dttol;

387:   /*
388:      View a graph of the current iterate
389:   */
390:   VecView(u, appctx->viewer2);

392:   /*
393:      Compute the exact solution
394:   */
395:   ExactSolution(time, appctx->solution, appctx);

397:   /*
398:      Print debugging information if desired
399:   */
400:   if (appctx->debug) {
401:     PetscPrintf(PETSC_COMM_SELF, "Computed solution vector\n");
402:     VecView(u, PETSC_VIEWER_STDOUT_SELF);
403:     PetscPrintf(PETSC_COMM_SELF, "Exact solution vector\n");
404:     VecView(appctx->solution, PETSC_VIEWER_STDOUT_SELF);
405:   }

407:   /*
408:      Compute the 2-norm and max-norm of the error
409:   */
410:   VecAXPY(appctx->solution, -1.0, u);
411:   VecNorm(appctx->solution, NORM_2, &norm_2);
412:   norm_2 = PetscSqrtReal(appctx->h) * norm_2;
413:   VecNorm(appctx->solution, NORM_MAX, &norm_max);

415:   TSGetTimeStep(ts, &dt);
416:   PetscPrintf(PETSC_COMM_WORLD, "Timestep %3" PetscInt_FMT ": step size = %g, time = %g, 2-norm error = %g, max norm error = %g\n", step, (double)dt, (double)time, (double)norm_2, (double)norm_max);

418:   appctx->norm_2 += norm_2;
419:   appctx->norm_max += norm_max;

421:   dttol = .0001;
422:   PetscOptionsGetReal(NULL, NULL, "-dttol", &dttol, NULL);
423:   if (dt < dttol) {
424:     dt *= .999;
425:     TSSetTimeStep(ts, dt);
426:   }

428:   /*
429:      View a graph of the error
430:   */
431:   VecView(appctx->solution, appctx->viewer1);

433:   /*
434:      Print debugging information if desired
435:   */
436:   if (appctx->debug) {
437:     PetscPrintf(PETSC_COMM_SELF, "Error vector\n");
438:     VecView(appctx->solution, PETSC_VIEWER_STDOUT_SELF);
439:   }

441:   return 0;
442: }
443: /* --------------------------------------------------------------------- */
444: /*
445:    RHSMatrixHeat - User-provided routine to compute the right-hand-side
446:    matrix for the heat equation.

448:    Input Parameters:
449:    ts - the TS context
450:    t - current time
451:    global_in - global input vector
452:    dummy - optional user-defined context, as set by TSetRHSJacobian()

454:    Output Parameters:
455:    AA - Jacobian matrix
456:    BB - optionally different preconditioning matrix
457:    str - flag indicating matrix structure

459:    Notes:
460:    Recall that MatSetValues() uses 0-based row and column numbers
461:    in Fortran as well as in C.
462: */
463: PetscErrorCode RHSMatrixHeat(TS ts, PetscReal t, Vec X, Mat AA, Mat BB, void *ctx)
464: {
465:   Mat         A      = AA;            /* Jacobian matrix */
466:   AppCtx     *appctx = (AppCtx *)ctx; /* user-defined application context */
467:   PetscInt    mstart = 0;
468:   PetscInt    mend   = appctx->m;
469:   PetscInt    i, idx[3];
470:   PetscScalar v[3], stwo = -2. / (appctx->h * appctx->h), sone = -.5 * stwo;

472:   /* - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
473:      Compute entries for the locally owned part of the matrix
474:      - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - */
475:   /*
476:      Set matrix rows corresponding to boundary data
477:   */

479:   mstart = 0;
480:   v[0]   = 1.0;
481:   MatSetValues(A, 1, &mstart, 1, &mstart, v, INSERT_VALUES);
482:   mstart++;

484:   mend--;
485:   v[0] = 1.0;
486:   MatSetValues(A, 1, &mend, 1, &mend, v, INSERT_VALUES);

488:   /*
489:      Set matrix rows corresponding to interior data.  We construct the
490:      matrix one row at a time.
491:   */
492:   v[0] = sone;
493:   v[1] = stwo;
494:   v[2] = sone;
495:   for (i = mstart; i < mend; i++) {
496:     idx[0] = i - 1;
497:     idx[1] = i;
498:     idx[2] = i + 1;
499:     MatSetValues(A, 1, &i, 3, idx, v, INSERT_VALUES);
500:   }

502:   /* - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
503:      Complete the matrix assembly process and set some options
504:      - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - */
505:   /*
506:      Assemble matrix, using the 2-step process:
507:        MatAssemblyBegin(), MatAssemblyEnd()
508:      Computations can be done while messages are in transition
509:      by placing code between these two statements.
510:   */
511:   MatAssemblyBegin(A, MAT_FINAL_ASSEMBLY);
512:   MatAssemblyEnd(A, MAT_FINAL_ASSEMBLY);

514:   /*
515:      Set and option to indicate that we will never add a new nonzero location
516:      to the matrix. If we do, it will generate an error.
517:   */
518:   MatSetOption(A, MAT_NEW_NONZERO_LOCATION_ERR, PETSC_TRUE);

520:   return 0;
521: }

523: PetscErrorCode IFunctionHeat(TS ts, PetscReal t, Vec X, Vec Xdot, Vec r, void *ctx)
524: {
525:   AppCtx *appctx = (AppCtx *)ctx; /* user-defined application context */

527:   MatMult(appctx->A, X, r);
528:   VecAYPX(r, -1.0, Xdot);
529:   return 0;
530: }

532: PetscErrorCode IJacobianHeat(TS ts, PetscReal t, Vec X, Vec Xdot, PetscReal s, Mat A, Mat B, void *ctx)
533: {
534:   AppCtx *appctx = (AppCtx *)ctx; /* user-defined application context */

536:   if (appctx->oshift == s) return 0;
537:   MatCopy(appctx->A, A, SAME_NONZERO_PATTERN);
538:   MatScale(A, -1);
539:   MatShift(A, s);
540:   MatCopy(A, B, SAME_NONZERO_PATTERN);
541:   appctx->oshift = s;
542:   return 0;
543: }

545: /*TEST

547:     test:
548:       args: -nox -ts_type ssp -ts_dt 0.0005

550:     test:
551:       suffix: 2
552:       args: -nox -ts_type ssp -ts_dt 0.0005 -time_dependent_rhs 1

554:     test:
555:       suffix: 3
556:       args:  -nox -ts_type rosw -ts_max_steps 3 -ksp_converged_reason
557:       filter: sed "s/ATOL/RTOL/g"
558:       requires: !single

560:     test:
561:       suffix: 4
562:       args: -nox -ts_type beuler -ts_max_steps 3 -ksp_converged_reason
563:       filter: sed "s/ATOL/RTOL/g"

565:     test:
566:       suffix: 5
567:       args: -nox -ts_type beuler -ts_max_steps 3 -ksp_converged_reason -time_dependent_rhs
568:       filter: sed "s/ATOL/RTOL/g"

570:     test:
571:       requires: !single
572:       suffix: pod_guess
573:       args: -nox -ts_type beuler -use_ifunc -ts_dt 0.0005 -ksp_guess_type pod -pc_type none -ksp_converged_reason

575:     test:
576:       requires: !single
577:       suffix: pod_guess_Ainner
578:       args: -nox -ts_type beuler -use_ifunc -ts_dt 0.0005 -ksp_guess_type pod -ksp_guess_pod_Ainner -pc_type none -ksp_converged_reason

580:     test:
581:       requires: !single
582:       suffix: fischer_guess
583:       args: -nox -ts_type beuler -use_ifunc -ts_dt 0.0005 -ksp_guess_type fischer -pc_type none -ksp_converged_reason

585:     test:
586:       requires: !single
587:       suffix: fischer_guess_2
588:       args: -nox -ts_type beuler -use_ifunc -ts_dt 0.0005 -ksp_guess_type fischer -ksp_guess_fischer_model 2,10 -pc_type none -ksp_converged_reason

590:     test:
591:       requires: !single
592:       suffix: fischer_guess_3
593:       args: -nox -ts_type beuler -use_ifunc -ts_dt 0.0005 -ksp_guess_type fischer -ksp_guess_fischer_model 3,10 -pc_type none -ksp_converged_reason

595:     test:
596:       requires: !single
597:       suffix: stringview
598:       args: -nox -ts_type rosw -test_string_viewer

600:     test:
601:       requires: !single
602:       suffix: stringview_euler
603:       args: -nox -ts_type euler -test_string_viewer

605: TEST*/